384 citations · 818 across the 11 of their papers we have counts for
12 papers · 1 filter
How to Train PointGoal Navigation Agents on a (Sample and Compute) Budget
Erik Wijmans, Irfan Essa, Dhruv Batra
PointGoal navigation has seen significant recent interest and progress, spurred on by the Habitat platform and associated challenge. In this paper, we study PointGoal navigation un…
Seeing the Un-Scene: Learning Amodal Semantic Maps for Room Navigation
Medhini Narasimhan, Erik Wijmans, Xinlei Chen +4
We introduce a learning-based approach for room navigation using semantic maps. Our proposed architecture learns to predict top-down belief maps of regions that lie beyond the agen…
Auxiliary Tasks Speed Up Learning PointGoal Navigation
Joel Ye, Dhruv Batra, Erik Wijmans +1
PointGoal Navigation is an embodied task that requires agents to navigate to a specified point in an unseen environment. Wijmans et al. showed that this task is solvable but their…
ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects
Dhruv Batra, Aaron Gokaslan, Aniruddha Kembhavi +5
We revisit the problem of Object-Goal Navigation (ObjectNav). In its simplest form, ObjectNav is defined as the task of navigating to an object, specified by its label, in an unexp…
Beyond the Nav-Graph: Vision-and-Language Navigation in Continuous Environments
Jacob Krantz, Erik Wijmans, Arjun Majumdar +2
We develop a language-guided navigation task set in a continuous 3D environment where agents must execute low-level actions to follow natural language navigation directions. By bei…
Analyzing Visual Representations in Embodied Navigation Tasks
Erik Wijmans, Julian Straub, Dhruv Batra +3
Recent advances in deep reinforcement learning require a large amount of training data and generally result in representations that are often over specialized to the target task. I…
Sim2Real Predictivity: Does Evaluation in Simulation Predict Real-World Performance?
Abhishek Kadian, Joanne Truong, Aaron Gokaslan +6
Does progress in simulation translate to progress on robots? If one method outperforms another in simulation, how likely is that trend to hold in reality on a robot? We examine thi…
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
Erik Wijmans, Abhishek Kadian, Ari Morcos +5
We present Decentralized Distributed Proximal Policy Optimization (DD-PPO), a method for distributed reinforcement learning in resource-intensive simulated environments. DD-PPO is…
The Replica Dataset: A Digital Replica of Indoor Spaces
Julian Straub, Thomas Whelan, Lingni Ma +27
We introduce Replica, a dataset of 18 highly photo-realistic 3D indoor scene reconstructions at room and building scale. Each scene consists of a dense mesh, high-resolution high-d…
Embodied Question Answering in Photorealistic Environments with Point Cloud Perception
Erik Wijmans, Samyak Datta, Oleksandr Maksymets +6
To help bridge the gap between internet vision-style problems and the goal of vision for embodied perception we instantiate a large-scale navigation task -- Embodied Question Answe…
Habitat: A Platform for Embodied AI Research
Manolis Savva, Abhishek Kadian, Oleksandr Maksymets +9
We present Habitat, a platform for research in embodied artificial intelligence (AI). Habitat enables training embodied agents (virtual robots) in highly efficient photorealistic 3…
Exploiting 2D Floorplan for Building-scale Panorama RGBD Alignment
Erik Wijmans, Yasutaka Furukawa
This paper presents a novel algorithm that utilizes a 2D floorplan to align panorama RGBD scans. While effective panorama RGBD alignment techniques exist, such a system requires ex…